Market Evolution: The Special Case When a Startup Has No Market Risk

In this post Steve Blank urges startup founders to consider what kind of risk they face if they want to be successful. They must figure out if they face technology risk, market risk or both? But I believe the key principle to understand here is market evolution.

In order to understand market evolution I think it’s helpful to dive a bit deeper into the special case where a startup has technology risk but no market risk, admittedly this occurs very rarely for web startups and is more likely the case for a life sciences startup. But this is still relevant for web startups because often you can gain deeper insights into an issue by understanding why something doesn’t apply than why it does.

The first key idea is that in even in cases where there is only technology risk and no market risk, the market still evolved out of nonexistence. If you identify that there’s only technology risk and no market risk for the startup you’re working on, than that’s because the market has already formed and there’s a lot of pent up demand as a result of no one being able to satisfy the market.

Steve Blank has classified market types a startup can be in into 3 major buckets, New, Existing and Resegemented (as niche or low cost).

For the purpose of mapping the possibility space of markets I’d like to add two more market types to the list: at the beginning, Non existent; and at the end, saturated/commoditized.

While new companies can’t play in non existent or saturated markets these stages are important additions to mapping the lifecycle of a market.

So now let’s take the canonical example of something that has only technology risk: finding a cure for cancer. There is clearly no market risk because if you developed this cure now, the world would beat a path to your door.

But while there is no market risk for cancer now, that hasn’t always been true, and it won’t always be true. The market for cancer cures, just like any market will will evolve through all these stages: nonexistent, new, existing, resegmented and saturated.

When is the market for cancer drugs nonexistent you ask?

For most of human history, actually. Since life expectancy has been below 40 for most of human history people died too early for cancer to have any relevance.

And even after human life expectancy began to rise to where cancer was killing people, there was still market risk, because first we had to discover what cancer was AND EDUCATE the public about cancer, before it would be possible to sell any kind of cancer treatment, even if it was invented.

One of the key points Steve emphasizes about new markets is that in order to grow the market, the potential customers must be educated. You can’t reliably sell someone what they don’t yet want or understand.

But the main point I want to emphasisze is that all markets are highly dependent on timing. Markets don’t exist for most of the time and when they do there are small windows of opportunity. The only time there is no market risk is when there is clearly an existing market, evidenced by extreme demand, but there are no companies serving this market because nobody has found a solution. There is only technologically risk here, because all you have to do is make the technological breakthrough to win.

Update: What this means for other industries

All industries face market risk. There are just a few problems where the market has evolved and technology has not been able to meet it.

Web tech has evolved to the point to where most applications face only market risk and no technology risk. We will eventually develop the tools and infrastructure to where new advances in the life sciences and in biotech only face market risk. The early signs of this are in Craig Venter’s research which will eventually allow us to program life in the same way we program machines. An industry transitions from facing both technology and market risk, to facing predominantly only market risk when creators stop focusing most of their energy question, “Can we even build this?” and instead focus on the efforts on the question “If we build this, will anybody want it?”

The 7 Variables You Need To Figure Out How To Apply Startup Advice To Your Startup

There are so many different perspectives about the right way to create a successful startup, how do we make sense of all this conflicting advice? Do you just have to figure out what works for you and stick to your guns? Assuming people are modeling the world correcting and not attributing their successes and failures to the wrong things, (which humans are extremely prone to!) can we piece different advice together to create a coherent picture of what actually works?

I believe by filtering advice through these 6 variables we can begin to stitch together the insights entrepreneurs are documenting everyday into unified schools of thought. The leading framework right now is the Lean Startup but I believe other internally consist schools of thought will soon emerge.

Most startup advice makes sense only if you take into account a number of variables to clarify the situation you’re talking about. Otherwise, people are usually both right, but talking past each other. I believe these 6 can bring clarity to to the startup advice & theory landscape.

(See my post here about how most advice that seems to conflict usually doesn’t.)

1) Life cycle of the startup Where is the startup on the continuum of Problem/Solution fit, Product/Market, Optimization, Scaling, and Transitioning to a Large Company.

You must clarify what stage of the startup you’re talking about. “Get as many users as you can” is great advice if you’ve found product/market fit, but it’s terrible advice if you haven’t.

2) Industry What industry are you in? (Web 2.0, Enterprise, Life sciences, Bio Tech, Social Entrepreneurship) Startups can come from many industries, by clarifying upfront what industry you are operating in you can understand what kinds of risks and constraints you’ll be facing, including Technology Risk, Market Risk, Capital Requirements, Intellectual Property and Government Regulations.

Technology risk is best understood as, “Can you make it”. Market risk is, “Will anybody buy it?”

3) Target Customer At a high level that means is it Business to Business (B2B) or Business to Consumer (B2C). But this question can be answered with increasing specificity, by stating more granular customer segments such as teens, CFO’s at fortune 1000’s or any Internet user with friends.

Don’t charge for your product initially so you can learn as much as possible about your users is good advice for a B2C property but if you give your product away to businesses they won’t take you seriously and kindly show you the door.

Sean Ellis preaches creating a product that creates extremely gratified users. That’s what you should strive for if you’re creating a consumer product, but you’re going to make more money selling lemonade and cotton candy to a business than selling them on how your product makes users feel good. Business don’t care about gratification, they care about ROI.

4) Business model How does your company create value and for whom? Do you charge for your product? (SaaS, Installed App) Do you give aspects of your product away for free? (Freemium) Do you monetize your users indirectly? (ad based). David Cohen has a great list here that I think covers most possible business models for Internet startups.

Driving a lot of traffic to your site and getting users to spend a lot of time with your product may make sense if you can monetize your users through ads, but if you have a freemium business model and your users aren’t buying your premium product you’ll just have a very expensive server bill at the end of the month and little revenue.

5) Network Effects Does your service get better the more people use it? Think Marketplaces, and Social Networks (eBay, Twitter, Facebook).

If you have a business with network effects getting users to pay for anything before they can begin contributing value is a very bad idea.

6) Market Type Are you in an existing market, a new market or resegmenting an existing market?

Hiring an amazing Marketing and PR team is a quick way to flush your money down the toilet if you’re in a new market, because getting your message out will not increase your revenue as the market hasn’t fully formed yet.

7) Expected Market Size Do you have the potential to be large high growth company? Or will your company max out as a small business?

If you’re market size is small, you’re wasting your time trying to get funding from VC’s.


Depending on the configuarion of these variables for your startup you’ll change the order for how you grow your business and validate your assumptions.

Steve Blank has an amazingly detailed workflow in Four Steps to the Epiphany that describes the whole life cycle of the startup (1) but you it only applies with a high degree of accuracy to enterprise B2B startups (2,3) that monetize customers directly (4), with no network effects (5) and are in a large market (7). (He clearly outlines the different strategies you should pursue depending on if you’re in an existing market, new market or a resegmented market (6).)

Ash Maurya has created a great workflow for the first two stages of the startup (1) Customer Discovery: reaching problem/solution fit and Customer Validation: reaching product/market fit that works for web 2.0 consumer startups (2,3) using a SaaS or premium business model (4), with no network effects (5), an existing or resegmented market (6), and can be adapted to any market size (7).

Note: I don’t think the way the positioning statement are developed work well for educating customers about a new market.

Andrew Chen describes why you may want to consider building a minimum desirable product rather than a minimum viable product. However this advice only applies to the Problem/Solution & Product/Market Fit stages (1) of a consumer web (2,3) startup, where users are likely monetized indirectly (4), there are network effects (5), is in a new or resegmented market (6) [otherwise what is desirable is already proven], and is shooting for a very large market (7).

Can this framework make sense of the debate between the Lean Startup and the Fat Startup?

I think Brant Cooper summarized it best with his tweet: “Fat vs Lean” C’mon now, people, money isn’t fat, it’s muscle. no money isn’t (necessarily) lean, it’s skinny.”

How much capital you raise depends most on your market size (7) and VC’s trust in you. How far along the startup is (1) often doesn’t even matter if your a successful veteran entrepreneur, VC’s will just give you a few million upfront and save you the headache of raising capital multiple times. The only drawback is that you can’t aim for an early exit.

How you spend money however is still heavily dependent on the stage of the startup (1). You want to keep burn as low as possible until you reach product market fit. And how you spend money on marketing (User Acquisition, Branding and PR) is highly dependent on Market Type (6).

This framework can also help you answer questions such as, how should you react to your competitors?

The first thing to do is to look at where you are in the lifecycle (1). If you are pre-scale, you should just ignore your competitors. Focus on playing your game.

The other most important variable is again Market Type, as it will guide all your marketing strategies. You’re also going to want a very deep understanding of your customer (3) and how much you can spend to gain market share, before the costs outweigh the benefits (7).

While there are certainly more variables, I believe these are most of the limited number of variables that will get you 80% of the way to understanding the right approach you should take.

What variables have I missed that should be included?

Reinventing Educational Will Come After Revolutionizing Entrepreneurial Learning

Below is an email I wrote to a friend about the implications of what I’m working on for the future of learning and education…

I got to this point by pivoting towards the vision of finding the future of learning.

I’ve been down in the details of startup culture for awhile so I forgot about this implication…

I actually believe if this format of support and learning is figured out with the most premium startups, it represents the future of learning and will trickle down to revolutionize education.

I think all the edu-startups have education wrong. They are trying to solve the problem through new ways of content delivery. But to transform education we have to look at how people actually learn and make an impact.

The best way to learn is very analogous to the lean startup. It’s about having a vision for something you want to do and then going and testing that hypothesis immediately by trying it. Whether it’s medicine, law, mechanical engineering or entrepreneurship. People need to test what it’s actually like as soon as possible and see if they can experience “flow” engaging in this activity.

The goal is to find something you really want to go deep into. John Seely Brown has my favorite quote in that regard, ““very often just going deeply into one or two topics that you really care about lets you appreciate the awe of the world … once you learn to honor the mysteries of the world, you’re kind of always willing to probe things … you can actually be joyful about discovering something you didn’t know … and you can expect always to need to keep probing. And so that sets the stage for lifelong inquiry.”

Another great quote from Steven Pinker is: “Accomplished people don’t bulk up their brains with intellectual calisthenics; they immerse themselves in their fields.” When colleges say they are teaching you how to think or building analytical rigor, this why it’s BS, because it doesn’t translate as well as they think it does.

Education is about supporting people to move through these 5 stages:
(1) No Desire — or intrinsic motivation (2) Desire to make an impact but uncertain about what, how or why (3) Possess an idea for a project but lack the knowledge and ability to know how to begin (4) A prototype has been built but need help gaining traction (5) The project has succeeded on a small scale but needs support going mainstream.

Essentially what Founders First will be doing is accelerating the A+ Founders who are very close to the finish line and then begin working backwards. The farther back you go there’s actually less a need to invent new things and more a need to just aggregate and streamline many of the programs that already exist to inspire young people and help them take the first step.

I wrote a quick post trying to adapt lean startup principles for education:

To Charge or to Learn: Pricing and Product Market Fit

A comment I left on this venturehacks post on pricing by Ash Maurya in which he quoted Sean Ellis:

I’m trying to reconcile the differences between your POV and Sean Ellis’.

I think first off it’s important to establish the goal: To get to product market fit.

Then that means the role of pricing is to maximize learning, which is how you will get to PMF fastest.

In some cases you need to charge users to maximize learning, otherwise they won’t take your product seriously enough to use it.

In other cases you learn more by letting users have access to everything, uninhibited.

I think it’s only useful to test price to maximize learning towards finding PMF, not for the reason to see if people will pay.

If people pay before PMF they are paying for a “nice to have” product by definition and that’s not a scalable, repeatable process. Their purchase is due to extraordinary circumstances, such as a hard sell by the founder, or the user was wealthy and didn’t mind paying for it after the trial was up, but ended up not sticking with the product.

“Will you pay for this?” is really just another way of saying do I have Product Market Fit – But it’s an inferior way of measuring PMF to the question, “Would you be disappointed if you could no longer use this?”. Paying customers are one way to measure if you have PMF but it’s a layer of abstraction above what you actually want. You can try to infer from pricing whether it means you have a must have product or not, but it’s harder to determine causality up a layer of abstraction.

It’s better just to measure directly whether people would be disappointed if they could no longer use it.

I think it’s also worth noting that you may have hit Product Market fit right off the bat with Cloud Fire. If someone is really good at Customer Discovery, which you are, that’s a possible scenario.

And in which case Sean would agree that you need to implement a business model and start charging right away.

The Long Tail of Innovation in an Information Economy

Once an innovation ecosystem has successfully created the structure to consistently tackle the big billion dollar opportunities, the system possesses the energy to begin evolving greater complexity, and squeezing out more efficiency. This efficiency will be realized by evolving the ecosystem to support the long tail of opportunities, which is exactly what the startup ecosystem is doing now.

Information age innovation ecosystems start by optimizing to hit the home run and can tolerate extremely high failure rates because the opportunity is so big. This is where venture money operates. Then the industry matures and seed and angel capital becomes more prevalent to support hitting multimillion dollar markets with greater consistency. I suspect for each industry an 80/20 power law applies: 80% of the wealth will be captured by a small number of billion dollar companies a la Google, Microsoft, Apple, Oracle, Facebook etc. but 80% of the opportunities (and 20% of the wealth) exist down the long tail. Just past the head of the power law exists collaboration products like Basecamp and publishing platforms WordPress. Further down the long tail exist products like Etherpad and Disqus. Farther still are where all the little tools and widgets that help us do day-to-day tasks just a little bit better, such as the popular iPhone App Shazam. In WordPress’ case it was a critical last piece to opening up blogging and self-publishing, which has transformed the way society shares information. Having a computer, the Internet, a rich web browser, and a really smart but not technically savvy person was not enough. We needed a simple publishing platform to crack the nut for self publishing.

So we need to create the proper surrounding ecology to make sure the long tail of innovation thrives. Without the right mix of capital, community, information and tools tuned for operating at this stage, the system will not come close to realizing all the opportunities that exist down the far end of the tail.

The incentives are strong for the individual, because even playing down the far end of the long tail is very lucrative and rewarding compared to an entry level corporate job, because you are working on something that matters, have passionate users and the potential to make millions. But the opportunity cost may be very high for those who are choosing between attempting to tackle billion dollar opportunities and opportunities down the long tail. So there are challenges in getting the top talent to tackle niche problems.

But I think it’s very important we figure how to tackle these problems as it’s a flourishing long tail of innovation that will both streamline and build resiliency into our systems. The long tail of products fill the many potholes that will enable us to run smoothly.

For example, I have a few friends who have a number of great ideas about how to solve email for in demand people who are always overloaded. This is a very important problem, that if solved could unlock a lot of productivity for society, because the influential can now more effectively communicate, delegate and make things happen. But the market is simply not that big. So how do talented entrepreneurs justify working on important niche projects vs. bigger problems they could sink their teeth into?

I’m not sure. Maybe they can treat it as a side project and let someone else do the scaling. Maybe as the entrepreneurial ecosystem gets more efficient entrepreneurs who were failing before, or people who weren’t even entrepreneurs before are now able to solve these problems.

Regardless of what the solution ends up being, it’s important we end up getting the incentives right so somebody is attacking these multimillion (but not billion) dollar niche opportunities. I think this last 20% may end up being what enables humanity’s solutions to finally outpace our problems. Achieving this escape velocity will be the difference in allowing the next stage of humanity to unfold.

Why Maximizing the Efficiency of the Startup Ecosystem Is Essential for Society’s Transition to an Information Economy

This post is a revision of written for emergent fool.

Right now the tech industry is the most innovative industry on the planet. Its success is in large part due to it being the first information age innovation ecosystem, which has implications for the future of the world, as we transition to an information economy.

This emerging information age is just the latest epochal shift of organized society as we have already progressed through tribal, agrarian and industrial societies. Now, on the cusp of this transition, the tech industry is pioneering the movement forward. (For more on this transition see Arthur Brock’s fantastic Prezi). Many of the methodologies and organizational structures that enhance a startup’s success will be relevant not just for startups but universal to the entire information age, because much of what works for tech startups will apply to emerging industries in the information economy. This is because innovation ecosystems that operate in the information age, are likely to operate in very similar ways, regardless of sector. The tech industry is just the first to inhabit space in the information economy and therefore is a harbinger for future industries.

The startup ecosystem is now creating the blueprint for the future of the information economy because much of the startup ecosystem replicated across emerging industries in sectors diverse as social change, health, biotech, molecular manufacturing and government, as soon as these industries begin their transition into the information age. Since the startup ecosystem will be replicated, it’s important to begin focusing on maximizing the efficiency now, both to increase the output of startups today, and to figure out how a more complete system works, so that we transfer a more stable, well-understood system. And since efficiencies realized in the tech ecosystem now will cascade over into the emerging industries, every further increase in efficiency will be amplified enormously and echo for generations, as it affects not just current startups, but all future copies of information age innovation ecosystems. The cheapest and therefore by definition, best place to experiment with improving innovation ecosystems for the entire information age is right here, right now in startup world. We must attempt to make our information age innovation ecosystems as robust as possible, because they represent the foundation of the future of the world’s economy.

If companies in these emerging industries want to maximize the scalability and impact of their solutions they will not only to need imitate the structure of the startup ecosystem but they will also need to draw heavily on the rules of the information economy that startups have begun to uncover. Their war chest will need to include tools and methods such as: social networks, crowdsourcing, the cloud, virtual collaboration, lean methodology, metrics and conversion funnels, customer development, rapid iteration, handling uncertainty and many other ideas now fundamental to a startup’s success.

You can already see some early signals of people and organizations in other sectors achieving great success by cross fertilizing principles and methdology from the startup world.

The Obama campaign changed political campaigns forever with their revolutionary level of citizen engagement. This was achieved by drawing heavily on Silicon Valley credo, with the campaign spearheaded by Chris Hughes, one of the co-founders of Facebook.

Kiva brought microfinance to the masses and has raised and distributed in an unprecedented amount of money by bridging the social sector with the operating principles of a Silicon Valley startup.

Government 2.0 is essentially an experiment asking the question, what happens if we mix Sillicon Valley with Government on a larger scale than campaigns, and use the power of data, transparency and API’s to increase the effectiveness of government? Health Care, Biotech and a slew of other industries are asking similar questions.

Hello Health is attempting to turn one aspect of the health care industry upside down by cutting insurance companies out of the doctor-patient relationship, simply by applying a few Silicon Valley startup principles to health care.

The tech industry has already changed the world, but as new industries adopt similar organizational principles society will experience multiplicative networks effects that will be utterly mind blowing. When people talk about accelerating change and the singularity and you don’t know what to expect, this it: when Silicon Valley leaves the valley and sweeps across the other industries of the world and transforms them into information age innovation ecosystems.

Information Age Innovation Ecosystems

If you look at the startup ecosystem’s output compared to all other industries over the last 30 years, you might dismiss it as an anomaly that will fade with time. But the industry’s incredibly fast wealth creation is not hype that will peter out, it’s a sign of what’s to come. The tech industry is just is the first of many information age innovation ecosystems, that will also be able to create a flurry of progress at an exponential rate.

The first requirement for an innovation ecosystem is that the core practice of an industry becomes an information technology. This is key because its information technology’s inherent scalability and replicability that enables exponential progress. The second critical requirement for an industry to become an innovation ecosystems is a large number of people freely experimenting. In the startup ecosystem, this was triggered by the personal computer and the mass amateurization of computing it allowed. When using a computer was incredibly complex and expensive the industry had a huge bottle neck. When that barrier was broken down and costs fell far enough that anyone could experiment in their bedroom or garage, the creativity of the masses was unleashed and amazing breakthroughs began to happen. That was the birth of the startup ecosystem.

I believe the birth of future innovation ecosystems, will occur the moment information technology can be used in the garage. Currently the startup ecosystem is the only scalable garage industry around, but imagine the creativity that will be unleashed as the costs fall far enough to allow other industries to enter garage territory. As soon as the garage threshold for biotech is crossed, an ecosystem similar to the startup ecosystem will begin to emerge. There will be firms dedicated to investing capital at various stages of the lifecycle of the company, communities of practice will emerge, formal conferences and informal meetups will spring up everywhere, databases of knowledge will be abundant, and open source infrastructure will be created that gives people even more leverage. Imagine people playing with atoms just as easily as they play with bits. Imagine biotech companies being born out of bedrooms and garages. The moment biotech becomes a fully functioning garage industry, with an efficient supporting ecosystem, the world is in for a crazy ride.

Again, this evolutionary process will apply not just to biotech but every industry with potential in an information economy. The 4 pillars of any innovation ecosystem I believe are Capital, Community, Information, and Tools.

Maximizing the Efficiency of the Startup Ecosystem

This post is a revision of written for emergent fool.

Over the last 3 decades the technology entrepreneurship sector has been the primary sector driving economic growth. The sector initiated the information economy and has given life to thousands of innovative companies, four of which are ten of the biggest companies in the United States, including Google, Apple, Microsoft and IBM. By any metric the sector has been wildly successful, but it’s possible to make the ecosystem even more efficient and realize an even greater number of opportunities.

Currently, projects that succeed are squeezing through a very tight bottle neck, and only the right combination of personality, skill and luck can breakthrough. Better infrastructure widens that bottle neck, so potential impact can be realized at a greater rate.

This post will look at how we can increase efficiency in the entrepreneurship ecosystem, but the significance of this effort may extend beyond the tech sector to the future of the information economy. My post on that topic is here.

Systems Perspective on Entrepreneurship

To increase efficiency further requires looking at the entrepreneurship ecosystem as a system in order to find the holes and the greatest points of leverage. But before we focus on improving the efficiency of system we need to understand the difference between the primary and secondary causes that drive innovation. There is nearly unanimous agreement that the most important players in the startup ecosystem are the founders and CEO’s who start from nothing and go on to create and control billion dollar markets. Society can’t stop glorifying entrepreneurs like Steve Jobs, Bill Gates and Richard Branson. But while they deserve immense praise and adulation the impact they are able to have has more to do with the surrounding innovation ecosystem than their individual ability and vision.

Something new and innovative can only be created and scaled if a confluence of forces come together— market, team, systems that allow you to find your team, capital, advice, cost of production, cost of distribution and culture (whether people are ready for it) etc. Breakthroughs are the result of way more than an individual with insight; they emerge from the last iteration of the system, building on top of existing tools and a huge history of knowledge.

Products and companies do make a huge impact but their success has more to do with the state and incentives of the system than the entrepreneur. It’s not the company that changes the world, it’s the system that creates the right incentives to make the creation of world changing breakthroughs extremely probable.

As the startup ecosystem has been fine tuned it has made the existence of certain products and companies almost inevitable, because the system exerts so much pressure to make opportunities come about once the timing is right. In Apple’s and Microsoft’s case there was immense pressure exerted on bringing about computer hardware and software companies.

If you are looking to bet on an individual company than a great entrepreneur is certainly the centerpiece. But if you want to maximize the innovation of a certain sector then you must look at the system, in this case the startup ecosystem. From the system perspective you just want a need to be filled and you don’t care who fills it. Thus the individual matters less, because there’s enough talent out there that if the incentives are strong enough someone will capitalize. But taking the system perspective far from trivializes the entrepreneur. In fact, talent development, which must have a very humanistic lens to be effective, is a critical part of an efficient startup ecosystem because potential talent needs to be actualized at a high rate.

The startup ecosystem is already extremely effective, just look around at the mark it has already left on the world in only a few decades, but if we want to make the system even more efficient and increase both the quality and quantity of innovative breakthroughs and great companies, we must identify places where friction is reducing the possibility of successful ventures and create solutions to remove this friction.

How The Startup Ecosystem Works Now

If we look at the rise of 3 of Silicon Valley’s fastest growing companies: Google, Facebook, and Twitter, in the context of the startup ecosystem it’s possible to see the existence of a category leader as almost inevitable, and the eventual winner as extremely unlikely. This matters because as long as someone can seize the opportunity and fill the market need, the battle from a macroeconomic perspective has already been won, it’s just a matter of which individual player will earn the spoils and how long they can maintain relevance before a new competitor overtakes them or the market becomes mature and commoditized.

Google, Facebook and Twitter now each dominate a category: Search, Social Networks and Microblogging, but there was plenty of competition and uncertainty at one point (remember Altavista, Yahoo, Myspace and Friendster? With better execution these companies could have also won). Once these categories were identified either consciously or by accident, the startup ecosystem was effective enough to support the formation of many teams, supplying them with capital, services, people, and advisors in hopes of capitalizing on a billion dollar market opportunity. And the team that executed the best won. The individual winner was unpredictable but the system was good enough to make sure someone won. That humans’ evolved a system that can create many competitors and then naturally select the winner based on merit or “fitness” is a tremendous accomplishment for this industry and for the world, and it is what makes tech the most innovative industry on the planet.

The success of these companies had a lot more to do the size of the market, the timing for when it was ready to be capitalized on and the resources in the startup ecosystem that supported effective scaling than the founders or the idea. The markets they operated in were big enough that inevitably an industry giant would emerge who would be able to use the lucrativeness of the market to generate a runaway positive feedback loop up until saturation, using their momentum to continually take market share and capture the best talent.

This evolutionary competitive process continues even after an industry giant has saturated a market, because there are always new markets emerging. While it would be very hard for Facebook and Google to screw up and concede supremacy in their primary markets, it is probable a new company will beat them in the new markets that they try to extend to that fall outside of their core competencies. (For more on why the market is the most important factor for a startup’s success check out this Marc Andressen’s post).

In summary, once the timing and conditions are ripe there will be enough people trying to tackle the clear billion dollar markets that somebody will get the execution right. The startup ecosystem is that good at providing all the puzzle pieces to make sure this happens!

Future billion dollar companies will ride trends such as the move to the cloud, mobile information, the real-time web, extreme personalization, and new kinds of data enabled by smaller and cheaper sensors.

The Evolving Startup Ecosystem

The tech industry has cracked the nut for how to tackle billion dollar market opportunities, making it better than any other industry at capitalizing on opportunity. But there is still a lot of room for growth. Increasing the effectiveness of the startup ecosystem matters as long as their are markets to be filled. The faster we can fill unmet with greater effectiveness the better off the world will be.

The tech ecosystem is now well tuned to hit the home run in billion dollar markets, but there is a shift happening as people began to realize there’s more opportunity and less risk to be had in aiming for singles and doubles, and hitting them consistently. The home runs of the previous era have created a new playing field and there is now a wealth of opportunities on the long tail with all kinds of business and consumer needs waiting to be met.

As the information economy has developed and become more complex, an increasing number of lucrative niches now make market sense to pursue. Whereas previously the opportunities either weren’t there (you couldn’t have a million dollar facebook app before facebook) or the costs were too high to have certain opportunities make sense (startups needed venture capitalists and VC’s only wanted to play in markets bigger than 100 million). But in recent years startups have become disentangled from their dependence on VC’s as the costs of starting a startup have continued to fall due to cheaper hardware and services moving to the cloud. This is driving a growing seed stage ecology where the primary actors are startup accelerators, angel investors and seed stage venture capitalists.

The focus now is on startups attacking smaller opportunities (though still in the 10’s of millions) with less investment capital. There will be an abundance of lucrative, unserved niches for startups to tackle. This coincides well with a number of trends:

– Science will be injected into the art of running a startup

Structure and methodology will be experimented with to increase the success rate of startups and startups will fail less because of self-destruction and more because of getting beat by competitors. As the overall number of startups in the ecosystem increase over the next few years, many of the startups in big markets will fail due to competitors, but in the huge number of opportunities in smaller markets startups will be more dispersed and there will be few direct competitors. In these markets startups that use a more scientific approach should be able to figure out how to hit the 10-100 million dollar markets with great consistency.

This consistency will enable the funding ecosystem to make sense for these smaller opportunities. When many investments are made in these smaller markets (<500 Million) the venture community’s approach of haphazardly throwing money at many petri dishes won’t work, because the upside potential is capped. Home run hitters can afford to strike out a lot, singles hitters can’t.

Even startups that lose to competitors in niche markets will find it easier to pivot, than pack it in and start from scratch, because the farther down the long tail you go the closer the adjacent verticals.

A fractal tree is a good analogy for why it’s easier to pivot in <100 million niches vs. billion dollar markets, if you consider the thickness of the branch equal to the size of the market. The core branches are very far apart. If your startup is set up to tackle a billion dollar opportunity it’s hard to pivot all the way over to another one, or shift gears and attack a smaller opportunity. But if you follow the analogy and you’re a startup attacking a niche as the tree branches further away from the trunk the twigs become closer together. The larger branches are too far away from each other to pivot from one to the other, but the small branches just require a little back tracking and a slight change in direction.

Creating a startup where the goal is to make something people want will still be a chaotic, iterative process but it’s possible to induce predictability and stability into chaotic systems.

– The potential for more collaboration horizontally and vertically across markets to create a more seamless experiences for the customer and more leverage for the startup. (I’ve started exploring this process, naming it the lego model)

– An increased demand for entrepreneurs due to clear ~10 million dollar opportunities just waiting to be tackled. This demand in the ecosystem for entrepreneurs coincides perfectly with changing cultural values about work, which will drive huge increase in the number of people pursuing entrepreneurship. And that in combination with a more entrepreneur friendly ecosystem evolving, will unleash a new golden age of entrepreneurship.

Here are two good posts on the changing seed stage ecology: Dave Mcclure’s presentation on the evolution of the startup ecosystem and Nathaniel Whittemore’s take on the seed stage ecology in the social sector..

New Efficiencies in the Startup Ecosystem

The startup ecosystem is certainly past its infancy, but it is still evolving rapidly and there are many more efficiencies to be unlocked that increase the success of startups further and support the long tail of innovation. Here’s my opinion on where we have opportunities to improve the system:

– Talent development

– Better conversion rate of people with ideas for companies, to entrepreneurs actually starting companies

– Pushing world’s brightest to choose entrepreneurship over other industries (college students starting companies instead of becoming an investment banker. Creating incentives for experienced execs to take risks starting something new instead of languishing in the rungs of the corporate ladder)

– Reducing friction in team formation, and better “deal flow” by interacting with more potential co-founders

– Aggregating startup services and service providers in order to remove distractions and allow startup teams to focus fully on the new innovation they’re trying to create

– Networks becoming more efficient in sharing assets (knowledge, people, code, strategy)

– More fluid and less cumbersome funding rounds, all the way from idea to scalable profitability

– Collaboration amongst startups to attack new verticals and interlink their advances to create networked impact— where success exists behind an activation energy only realizable by coordinated efforts of multiple startups

– Connecting entrepreneurs to the people and information at the time they need to support maximization of potential— time and energy will consistently be put in highest leverage places

– Better filters by injecting personalization and social graph into many tools

– Systems that use psychology and persuasion to nudge people to act in their own long term self interest, mitigating human kind’s insidious propensity for short term thinking

And what I’m personally targeting right now with Founders First: accelerated just in time learning.

Finally, a few projects and trends I think are very important:

Rise of startup accelerators and therefore an emerging market for post-startup accelerators and pre-startup accelerators. (I’m working on the post startup accelerator phase with Founders First. See all the new startup accelerators here and many of the companies here)

Venture Hacks Angel List and Startup List to reduce friction in the funding of startups.

Right Side Capital Management— A new kind of investment fund trying to dramatically increase deal flow to 100-200 investments a year. This will support faster expansion into niches.

The Connecting Thread: The Innovation Landscape

One of the primary stitches running across my life cloak:

The primary engine driving economic growth is innovation. And we are in the midst of transitioning to a new innovation landscape as corporations are dying and the startup ecosystem matures. The innovation landscape is the overlapping theme for most of what I’m thinking about and working on. I’m interested in how we can increase collaboration, access more capital, push the interconnectivity and support systems a step further and increase the overall size of the ecosystem by getting more aspiring entrepreneurs across the chasm of commitment.

The innovation landscape is intimately related to what I believe is the world’s biggest problem and the approach we need to solve it. I discuss that in the 5 stages post, linked below.

A few of my frameworks for thinking about the innovation space: (Posts will soon be written for all of these)

Pre-Accelerator. Accelerator. Post Accelerator.

5 stages of the entrepreneurial journey

Startups engaging collaboratively in complex value chains to achieve the scale of corporations, called the Lego Model and described here.

The 4 Pillars of Innovation Landscape: Community, Information, Tools, Capital. Most projects are different proportions of these 4 elements.

The innovation space is incredibly complex requiring a variety of different perspectives and knowledge on a wide array of subjects. This overarching theme connects my many interests: (I find the “I, it, we, its” a helpful organizing framework) I: talent development, psychology, learning, education, mental technologies; It: Personal productivity, food, athletic, health, energy management; We: community, social interaction, culture, collaboration; Its: geopolitics, interconnectedness, foresight, accelerating technological change, startups, behavioral economics, environmental sustainability, systems thinking;